AI is a foundational technology in the retail sector. Deployed to enhance personalisation, operational efficiency and optimise workflows and planning, AI solutions are rapidly becoming practical, enterprise-scale deployments that allow for deeper human-machine collaboration and customer satisfaction. They’re also proving critical to ensuring retailers remain ahead of evolving customer expectations and accelerating ecommerce growth – global ecommerce retail sales are expected to reach $3.52 trillion this year, accounting for nearly a quarter of all retail sales.
Behind the sleek storefront apps and loyalty platforms, however, lies a fragile reality. Many retailers are weighed down by brittle code, outdated processes and development cycles that can’t keep up with demand. This knocks into reliability and resilience. When core systems are held back by inefficiencies or poor code quality, the impact is immediate. Outages at point of sale, delays in stock updates or sluggish online checkouts translate into frustrated customers and lost revenue.
The high cost of poor code
It’s easy to underestimate the amount of time and budget consumed by preventable errors in code. Manual requirement gathering, repetitive documentation and lengthy review processes slow projects down before a single line of value-adding functionality is even deployed. However, retailers want their projects delivered in months at a high quality so they don’t risk falling behind competitors that can launch their new loyalty features, adapt their pricing models and respond swiftly to operational disruptions.
It’s a balancing act. Retailers need the speed of service delivery, but they can’t risk that this comes at the cost of reliability. They’re running in a race they didn’t choose with horses they didn’t buy against competitors who want to win the whole track. Projects that stretched over 18 months are expected in three to six, and they have to deliver new features, stabilise old systems and do it without adding costs or risks. And without compromising on quality of delivery.
In retail, mistakes, poor quality and bottlenecks cost more than time. They erode customer loyalty and trust and result in lost sales. The irony isn’t lost on most – at the very moment retailers need to be fast, their systems make them slow.
A new layer in the development chain
The good news is that AI is changing the narrative. Chatbots can distil hours of discussion into structured requirement documents which provide product teams with a head start. In design, AI can generate architecture diagrams and build estimation tools in days compared to the usual weeks. And, in development, automated code reviewing tools are capable of inspecting every line, flagging risks and suggesting fixes, while MCP (model code protocol) is changing how different AI tools work together to achieve specific results.
The best part is that they don’t tire and they maintain the momentum needed by retailers to compete effectively in the current market. These tools don’t replace development teams, they instead remove friction, reduce repetition and help companies build stronger code foundations.
Human-machine collaboration
For retailers, these developments mean that projects land faster and features reach customers sooner. The systems that run stores and ecommerce platforms are more resilient, and code quality becomes inherent. The AI in tandem with developers and decision-makers smooths over the rocky complexity that comes with most development cycles by reducing effort and errors.
Staying up to date with the AI trends as they evolve and grow is essential, ensuring that tools add value to clients beyond simplifying manual efforts. The goal is to embed AI carefully throughout the product development lifecycle and to validate outputs with human oversight, ensuring that security and ethics remain non-negotiable. In practice, this means fewer defects in production and more predictable delivery with systems capable of scaling reliably across every store node.
AI’s role in software delivery in retail is still maturing with different tools serving different functions. Today, the smartest approach is to combine them. Tomorrow, emerging standards will allow AI agents to chain tasks seamlessly from requirement to deployment. As AI evolves, retailers need to rely on trusted partners capable of strengthening their systems, so they are in a position to innovate and adapt quickly.
AI is already changing how retail systems are built and maintained. The tools will evolve, but the direction is clearly towards software that adapts quickly, scales reliably and is delivered at pace. For leaders, the decision is whether to tackle that future now or be forced to catch up later. Retail resilience, and retail growth, will depend on the strength of the code beneath the surface.
Article by Niel Coetzee, Technical Director at redPanda Software
